Fengbei Liu
Orcid: 0000-0003-0355-2006
According to our database1,
Fengbei Liu
authored at least 32 papers
between 2020 and 2024.
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Bibliography
2024
An Interpretable and Accurate Deep-Learning Diagnosis Framework Modeled With Fully and Semi-Supervised Reciprocal Learning.
IEEE Trans. Medical Imaging, January, 2024
Medical Image Anal., 2024
Effective Segmentation of Post-Treatment Gliomas Using Simple Approaches: Artificial Sequence Generation and Ensemble Models.
CoRR, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images.
Medical Image Anal., December, 2023
Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable Image Classification.
CoRR, 2023
Generative Noisy-Label Learning by Implicit Dicriminative Approximation with Partial Label Prior.
CoRR, 2023
CoRR, 2023
Unsupervised Anomaly Detection in Medical Images with a Memory-Augmented Multi-level Cross-Attentional Masked Autoencoder.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation.
CoRR, 2022
CoRR, 2022
Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder.
CoRR, 2022
Semantic-guided Image Virtual Attribute Learning for Noisy Multi-label Chest X-ray Classification.
CoRR, 2022
Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes.
Proceedings of the Computer Vision - ECCV 2022, 2022
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
ACPL: Anti-curriculum Pseudo-labelling forSemi-supervised Medical Image Classification.
CoRR, 2021
Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation.
CoRR, 2021
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021
3D Semantic Mapping from Arthroscopy Using Out-of-Distribution Pose and Depth and In-Distribution Segmentation Training.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning.
IEEE Access, 2020
Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020